On the Verification of Belief Programs
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Abstract (arXiv)
In a recent paper, Belle and Levesque proposed a framework for a type of program called belief programs, a probabilistic extension of GOLOG programs where every action and sensing result could be noisy and every test condition refers to the agent's subjective beliefs. Inherited from GOLOG programs, the action-centered feature makes belief programs fairly suitable for high-level robot control under uncertainty. An important step before deploying such a program is to verify whether it satisfies properties as desired. At least two problems exist in doing verification: how to formally specify properties of a program and what is the complexity of verification. In this paper, we propose a formalism for belief programs based on a modal logic of actions and beliefs. Among other things, this allows us to express PCTL-like temporal properties smoothly. Besides, we investigate the decidability and undecidability for the verification problem of belief programs.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 34 references that are in the map. First posted on arXiv 26 Apr 2022.
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References · 6
- 2020The Probabilistic Model Checker Stormcited by 64
- 2013What is Decidable about Partially Observable Markov Decision Processes with ω-Regular Objectivescited by 14
- 2014Optimal Cost Almost-sure Reachability in POMDPscited by 12
- 2020Verification of indefinite-horizon POMDPscited by 8
- 2022Under-Approximating Expected Total Rewards in POMDPscited by 5
- 2018Reasoning about Discrete and Continuous Noisy Sensors and Effectors in Dynamical Systemscited by 2
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